Passion for AI systems at scale: You’ve worked on LLM, ML platform, data, or infrastructure teams that own critical shared systems. You understand the challenges of scaling reliability, latency, cost, and quality as usage and model complexity grow. You care deeply about building platforms that are dependable, efficient, and easy for other engineers to use
Adaptable and curious: You like going deep on how systems behave in practice, especially when models, providers, and product requirements are changing quickly. You’re eager to use AI tools to work smarter and are willing to move across backend, infrastructure, libraries, and product code when that’s what the problem requires
Extreme ownership: You’re comfortable working across ambiguous problem spaces, aligning stakeholders around a clear path forward, and driving execution with accountability. You take ownership of platform outcomes including reliability, quality, adoption, and operational follow-through beyond team boundaries
Thoughtful problem-solving: For you, problem-solving starts with a clear and accurate understanding of the context. You can decompose ambiguous system behavior, debug across layers, and work toward clean, pragmatic solutions by yourself or with teammates. You’re comfortable asking for help when you get stuck
Pragmatic and business-oriented: You understand that AI platform work is full of tradeoffs across quality, latency, cost, reliability, and speed of execution. You prioritize based on product and business impact, balancing craft with urgency and operational simplicity
2-4 years of experience as a Software Engineer
Experience with applied AI product development (prompting, evals, model integrations, or quality measurement)
You've built out and scaled data processing pipelines at scale with Apache Spark or Ray
You’ve past experience working full-stack in Typscript and node.js ecosystem
You have experience building MLOps and ML serving infrastructure
A NOTE ON AI
You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on